TypeError with the python script do_fit.py

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4 years 4 months ago #8363 by Hot

TypeError with the python script do_fit.py was created by Hot

I am doing CG simulation and initial guess for angle bending parameters，according to http://cgmartini.nl/index.php/tutorials-general-introduction-gmx5/bilayers-gmx5#Adv-refinehttp://cgmartini.nl/index.php/tutorials-general-introduction-gmx5/bilayers-gmx5#Adv-refine .
The python script do_fit.py was used, and the command is as follows:
python do_fit.py -f ANGLES/cga_0-distr.xvg -x0 100 -k 400 --harmonic --radians

Returned results：
Parameter Value Standard Deviation
par_0 1.055004e+02 4.039648e-01
par_1 8.000000e+02 1.338068e+02
Status message CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
Number of iterations 4
Objective <symfit.core.objectives.LeastSquares object at 0x2ae29ab84810>
Minimizer <symfit.core.minimizers.LBFGSB object at 0x2ae29ab67650>

Goodness of fit qualifiers:
chi_squared 0.631567762071
objective_value 0.315783881035
r_squared 0.679987456214
Traceback (most recent call last):
File "do_fit.py", line 135, in <module>
plt.plot(xs, model(x=xs, **result.params), color='r')
File "/home/stjt/miniconda3/envs/do-fit/lib/python2.7/site-packages/symfit/core/operators.py", line 90, in call
bound_arguments = signature.bind(*values, **relevant_named_values)
File "/home/stjt/miniconda3/envs/do-fit/lib/python2.7/site-packages/funcsigs/__init__.py", line 792, in bind
return args[0]._bind(args[1:], kwargs)
File "/home/stjt/miniconda3/envs/do-fit/lib/python2.7/site-packages/funcsigs/__init__.py", line 717, in _bind
raise TypeError(msg)
TypeError: 'var_0' parameter lacking default value

Where need to modify？

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peterkroon
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4 years 4 months ago #8365 by peterkroon

Replied by peterkroon on topic TypeError with the python script do_fit.py

Hi,

to be honest, I haven't looked at or maintained that script in quite some time.

First, upgrade to Python3. After January 1 2020 Python2 will no longer be supported by anyone in the world.
Then, for the script:
In lines 110-112:

x = Variable() * args.factor
x0 = Parameter(value=args.x0, min=np.min(xs), max=np.max(xs)) * args.factor
k = Parameter(value=args.k, min=args.mink, max=args.maxk)

Should be:

x = Variable('x') * args.factor
x0 = Parameter('x0', value=args.x0, min=np.min(xs), max=np.max(xs)) * args.factor
k = Parameter('k', value=args.k, min=args.mink, max=args.maxk)

Line 135:

plt.plot(xs, model(x=xs, **result.params), color='r')

should be

plt.plot(xs, model(x=xs, **result.params)[0], color='r')

Let me know if it works, so I can update the tutorial files.

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Hot
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4 years 4 months ago #8366 by Hot

Replied by Hot on topic TypeError with the python script do_fit.py

I have modified the script following your prompt，and run it with Python2 and Python3 respectively. The error still exists.
Python2:
/home/miniconda3/envs/do-fit/lib/python2.7/site-packages/symfit/core/fit_results.py:114: RuntimeWarning: invalid value encountered in sqrt
return np.sqrt(self.variance(param))

Parameter Value Standard Deviation
par_0 9.800000e+01 nan
par_1 5.000000e+01 3.055364e+01
Status message CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
Number of iterations 2
Objective <symfit.core.objectives.LeastSquares object at 0x2b15e24577d0>
Minimizer <symfit.core.minimizers.LBFGSB object at 0x2b15e243b610>

Goodness of fit qualifiers:
chi_squared 5.44559526318
objective_value 2.72279763159
r_squared -1.75925862157
Traceback (most recent call last):
File "do_fit.py", line 135, in <module>
plt.plot(xs, model(x=xs, **result.params), color='r')
File "/home/stjt/miniconda3/envs/do-fit/lib/python2.7/site-packages/symfit/core/operators.py", line 90, in call
bound_arguments = signature.bind(*values, **relevant_named_values)
File "/home/stjt/miniconda3/envs/do-fit/lib/python2.7/site-packages/funcsigs/__init__.py", line 792, in bind
return args[0]._bind(args[1:], kwargs)
File "/home/stjt/miniconda3/envs/do-fit/lib/python2.7/site-packages/funcsigs/__init__.py", line 717, in _bind
raise TypeError(msg)
TypeError: 'var_0' parameter lacking default value

Python3:
do_fit.py:92: DeprecationWarning: inspect.getargspec() is deprecated since Python 3.0, use inspect.signature() or inspect.getfullargspec()
if 'n' not in inspect.getargspec(args.func).args and hasattr(args, 'n'):
do_fit.py:95: DeprecationWarning: inspect.getargspec() is deprecated since Python 3.0, use inspect.signature() or inspect.getfullargspec()
if not hasattr(args, 'n') and 'n' in inspect.getargspec(args.func).args:
do_fit.py:110: DeprecationWarning: It is recommended to provide names to Variable explicitly as automatic generation of names will be dropped in future `symfit` versions.
x = Variable() * args.factor
qt.qpa.xcb: QXcbConnection: XCB error: 145 (Unknown), sequence: 177, resource id: 0, major code: 139 (Unknown), minor code: 20
/home/stjt/miniconda3/lib/python3.7/site-packages/symfit/core/fit_results.py:114: RuntimeWarning: invalid value encountered in sqrt
return np.sqrt(self.variance(param))

Parameter Value Standard Deviation
par_0 9.800000e+01 nan
par_1 5.000000e+01 3.055364e+01
Status message b'CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL'
Number of iterations 2
Objective <symfit.core.objectives.LeastSquares object at 0x2aca22deaf90>
Minimizer <symfit.core.minimizers.LBFGSB object at 0x2aca22deaad0>

Goodness of fit qualifiers:
chi_squared 5.4455952631815085
objective_value 2.7227976315907543
r_squared -1.759258621573057
Traceback (most recent call last):
File "do_fit.py", line 135, in <module>
plt.plot(xs, model(x=xs, **result.params), color='r')
File "/home/stjt/miniconda3/lib/python3.7/site-packages/symfit/core/operators.py", line 90, in call
bound_arguments = signature.bind(*values, **relevant_named_values)
File "/home/stjt/miniconda3/lib/python3.7/inspect.py", line 3015, in bind
return args[0]._bind(args[1:], kwargs)
File "/home/stjt/miniconda3/lib/python3.7/inspect.py", line 2930, in _bind
raise TypeError(msg) from None
TypeError: missing a required argument: 'var_0'

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peterkroon
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4 years 4 months ago #8371 by peterkroon

Replied by peterkroon on topic TypeError with the python script do_fit.py

Interesting :)

While I start digging, could you get me the output of

pip show symfit

?

And could you double check you made all the modifications?

File "do_fit.py", line 135, in <module>
plt.plot(xs, model(x=xs, **result.params), color='r')

still looks like the old code.

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peterkroon
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4 years 4 months ago #8372 by peterkroon

Replied by peterkroon on topic TypeError with the python script do_fit.py

Ok, I made some modifications and get the following output:

$ python3 -V
Python 3.6.8

$ pip3 show symfit
Name: symfit
Version: 0.5.2
...

$ python3 do_fit.py -f ANGLES/cga_0-distr.xvg -x0 135 -k 35 --harmonic --radians

Parameter Value        Standard Deviation
k         1.878271e+01 4.340405e-01
x0        1.317686e+02 2.847421e-01
Status message         b'CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH'
Number of iterations   10
Objective              <symfit.core.objectives.LeastSquares object at 0x7feff9425a58>
Minimizer              <symfit.core.minimizers.LBFGSB object at 0x7feff942eba8>

Goodness of fit qualifiers:
chi_squared            0.4169061723299059
objective_value        0.20845308616495295
r_squared              0.9715937509657963

And for Python2:

$ python2 -V
Python 2.7.15+

$ pip2 show symfit
Name: symfit
Version: 0.5.2
...

$ python2 do_fit.py -f ANGLES/cga_0-distr.xvg -x0 135 -k 35 --harmonic --radians

Parameter Value        Standard Deviation
k         1.878271e+01 4.340405e-01
x0        1.317686e+02 2.847421e-01
Status message         CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH
Number of iterations   10
Objective              <symfit.core.objectives.LeastSquares object at 0x7f373456f350>
Minimizer              <symfit.core.minimizers.LBFGSB object at 0x7f375fb9fcd0>

Goodness of fit qualifiers:
chi_squared            0.41690617233
objective_value        0.208453086165
r_squared              0.971593750966

The changes I made:

$ diff do_fit_original.py do_fit.py
8c8
< from symfit.api import exp, cos, Variable, Parameter, Fit
---
> from symfit import exp, cos, Variable, Parameter, Fit, Model
110,112c110,113
< x = Variable() * args.factor
< x0 = Parameter(value=args.x0, min=np.min(xs), max=np.max(xs)) * args.factor
< k = Parameter(value=args.k, min=args.mink, max=args.maxk)
---
> y = Variable('y')
> x = Variable('x') * args.factor
> x0 = Parameter('x0', value=args.x0, min=np.min(xs), max=np.max(xs)) * args.factor
> k = Parameter('k', value=args.k, min=args.mink, max=args.maxk)
117c118
<     n = Parameter(value=args.n, min=0, max=args.n * 2, fixed=True)
---
>     n = Parameter('n', value=args.n, min=0, max=args.n * 2, fixed=True)
122c123
< model = harmonic_distribution(**argument_dict)
---
> model = Model({y: harmonic_distribution(**argument_dict)})
124c125
< guess = symfit.contrib.interactive_guess.interactive_guess.InteractiveGuess2D(model, xs, ys) 
---
> guess = symfit.contrib.interactive_guess.interactive_guess.InteractiveGuess2D(model, x=xs, y=ys) 
129c130
< fit = Fit(model, xs, ys)
---
> fit = Fit(model, x=xs, y=ys)
135c136
< plt.plot(xs, model(x=xs, **result.params), color='r')
---
> plt.plot(xs, model(x=xs, **result.params).y, color='r')

Could you give these a try? If this doesn't work for you there's something very strange going on, and I'll have to dig deeper. If it works for you I'll update the tutorial.

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Hot
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4 years 4 months ago #8373 by Hot

Replied by Hot on topic TypeError with the python script do_fit.py

I have modified do-fit.py and get the output:
symfit 0.5.2
Python3.7.3
do_fit.py:92: DeprecationWarning: inspect.getargspec() is deprecated since Python 3.0, use inspect.signature() or inspect.getfullargspec()
if 'n' not in inspect.getargspec(args.func).args and hasattr(args, 'n'):
do_fit.py:95: DeprecationWarning: inspect.getargspec() is deprecated since Python 3.0, use inspect.signature() or inspect.getfullargspec()
if not hasattr(args, 'n') and 'n' in inspect.getargspec(args.func).args:
Traceback (most recent call last):
File "do_fit.py", line 122, in <module>
model = Model({y: harmonic_distribution(**argument_dict)})
File "do_fit.py", line 43, in boltzmann
return exp(-V(*args, **kwargs)/kbT)
File "do_fit.py", line 47, in harmonic
return 0.5 * k * (x - x0)**2
TypeError: unsupported operand type(s) for *: 'float' and '_StoreAction'

Python2.7
Traceback (most recent call last):
File "do_fit.py", line 122, in <module>
model = Model({y: harmonic_distribution(**argument_dict)})
File "do_fit.py", line 43, in boltzmann
return exp(-V(*args, **kwargs)/kbT)
File "do_fit.py", line 47, in harmonic
return 0.5 * k * (x - x0)**2
TypeError: unsupported operand type(s) for *: 'float' and '_StoreAction'

The result is different from yours. I don't know what the problem is.

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peterkroon
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4 years 4 months ago #8381 by peterkroon

Replied by peterkroon on topic TypeError with the python script do_fit.py

Very strange.

It also works for me on Python 3.7.4 (although I do get the deprecation warning about inspect.signature).
Could you try `pip install --force-reinstall symfit matplotlib`? My guess is your sympy version got too old (1.4 here; `pip show sympy`).

I'll put my full code below, just to be sure.

Warning: Spoiler! [ Click to expand ]

from symfit import exp, cos, Variable, Parameter, Fit, Model
import symfit.contrib
import numpy as np
import functools
import matplotlib.pyplot as plt
import argparse
import os
import inspect

kb = 8.3144621e-3  # kJ/mol/K
T = 298


def read_xvg(file_name):
    #return np.loadtxt(file_name, comments = '@', dtype=np.float)
    #Let's assume simply tabulated data for now (x y\nx y\nx y...)
    data = []
    comment_chars = ('#', '@')
    with open(file_name, 'r') as file_handle:
        for line in file_handle:
            line = split_comments(line, comment_chars)[0].strip()
            if not line:
                continue
            data.append(list(map(float, line.split())))
    return np.array(data, dtype=float)


def split_comments(line, comment_chars):
    find = lambda char: (line.find(char), char) if char in line else (len(line), char)
    comment_start, char = min(map(find, comment_chars), key=lambda x: x[0])
    return line[:comment_start], line[comment_start + len(char):]


def boltzmann(T, V, *args, **kwargs):
    kbT = kb * T
    return exp(-V(*args, **kwargs)/kbT)


def harmonic(x, x0, k):
    return 0.5 * k * (x - x0)**2


def periodic(x, x0, k, n):
    return k*(1+cos(n*x - x0))


funcs = {'harmonic': harmonic, 'periodic': periodic}


def file_readable(file):
    if not os.access(file, os.F_OK | os.R_OK):
        raise argparse.ArgumentTypeError("{} is not readable or does not exist.".format(file))
    return file


parser = argparse.ArgumentParser(description="Fit a function to data.")


parser.add_argument('-f', help='(input) XVG file containing the data to fit to',
                    required=True, metavar='data.xvg', type=file_readable, dest='xvg_file')
function_group = parser.add_mutually_exclusive_group(required=True)

function_group.add_argument('--harmonic', help='use an harmonic functional (V(x) = 0.5 * k * (x - x0)**2)', action='store_const', const=harmonic, dest='func')
function_group.add_argument('--periodic', help='use an periodic functional (V(x) = k * (1 + cos(n*x - x0)))', action='store_const', const=periodic, dest='func')
x0 = parser.add_argument('-x0', help='equilibrium value.', required=True,
                    type=float, dest='x0')
k = parser.add_argument('-k', help='force constant.', required=True,
                    type=float, dest='k')
parser.add_argument('-mink', help='(opt.) minimum value allowed for k.', required=False, default=0, type=float, metavar=0)
parser.add_argument('-maxk', help='(opt.) maximum value allowed for k.', required=False, default=None, type=float, metavar='2*k')
n = parser.add_argument('-n', help='(opt.) periodicity for periodic function.',
                    required=False, type=int, dest='n', metavar=1)
parser.add_argument('--radians', '-rad', help='(opt.) specify whether x0 and the x-axis in your data should be converted to radians. This is usually the case for all angles.',
                    required=False, action='store_const', const=np.pi/180, default=1, dest='factor')
parser.add_argument('-T', help='(opt.) temperature (K).',
                    required=False, default=298, type=float, dest='T', metavar=298)
args = parser.parse_args()

if args.maxk is None:
    args.maxk = args.k * 2

if args.n is None:
    del args.n

if 'n' not in inspect.getargspec(args.func).args and hasattr(args, 'n'):
    raise argparse.ArgumentError(n, 'This function type does not accept -n.')

if not hasattr(args, 'n') and 'n' in inspect.getargspec(args.func).args:
    args.n = 1



data = read_xvg(args.xvg_file)

xs = data[:, 0]
ys = data[:, 1]
ys = ys/np.max(ys)  # Normalize data


harmonic_distribution = functools.partial(boltzmann, args.T, args.func)

argument_dict = {}
y = Variable('y')
x = Variable('x') * args.factor
x0 = Parameter('x0', value=args.x0, min=np.min(xs), max=np.max(xs)) * args.factor
k = Parameter('k', value=args.k, min=args.mink, max=args.maxk)
argument_dict['x'] = x
argument_dict['x0'] = x0
argument_dict['k'] = k
if hasattr(args, 'n'):
    n = Parameter('n', value=args.n, min=0, max=args.n * 2, fixed=True)
    argument_dict['n'] = n



model = Model({y: harmonic_distribution(**argument_dict)})
#fit = fitter.InteractiveFit2D(model, xs, ys)
guess = symfit.contrib.interactive_guess.interactive_guess.InteractiveGuess2D(model, x=xs, y=ys) 
#fit.visual_guess(1000)
#result = fit.execute(maxfev=1000)
result = guess.execute()

fit = Fit(model, x=xs, y=ys)
result = fit.execute()

print(result)

plt.scatter(xs, ys, color='b')
plt.plot(xs, model(x=xs, **result.params).y, color='r')
plt.show()

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TypeError with the python script do_fit.py